title: DBS artifact suppression using a time-frequency domain filter.
abstract: Electroencephalogram (EEG) is a useful tool for brain research. However, during Deep-Brain Stimulation (DBS), there are large artifacts that obscure the physiological EEG signals. In this paper, we aim at suppressing the DBS artifacts by means of a time-frequency-domain filter. As a pre-processing step, Empirical-Mode Decomposition (EMD) is applied to detrend the raw data. The detrended signals are then filtered iteratively until, by visual inspection, the quality is good enough for interpretation. The proposed algorithm is demonstrated by an application to a clinical DBS-EEG data set in resting state and in finger-tapping condition. Moreover, a comparison with a Low-Pass filter (LPF) is provided, by visual inspection and by a quantitative measure.
authors.forename: Alina
authors.initials: A
authors.lastname: Santillán-Guzmán
authors.forename: Ulrich
authors.initials: U
authors.lastname: Heute
authors.forename: Muthuraman
authors.initials: M
authors.lastname: Muthuraman
authors.forename: Ulrich
authors.initials: U
authors.lastname: Stephani
authors.forename: Andreas
authors.initials: A
authors.lastname: Galka
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000502:physiology; D046690:Deep Brain Stimulation / Q000379:methods*; D005385:Fingers; D006801:Humans; D012146:Rest / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors